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E-raamat: Analyzing Data with Power BI and Power Pivot for Excel

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  • Formaat: 256 pages
  • Sari: Business Skills
  • Ilmumisaeg: 28-Apr-2017
  • Kirjastus: Microsoft Press
  • Keel: eng
  • ISBN-13: 9781509302819
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Analyzing Data with Power BI and Power Pivot for ExcelSuurem pilt
  • Formaat: 256 pages
  • Sari: Business Skills
  • Ilmumisaeg: 28-Apr-2017
  • Kirjastus: Microsoft Press
  • Keel: eng
  • ISBN-13: 9781509302819
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Introduces the basic techniques for shaping data models in Excel and Power BI, covering such topics as analyzing date and time intervals, tracking historical attributes, and using multiple fact tables.

The first complete guide to data modeling in Power BI and Power Pivot helps users build models that will help them transform data into actionable insight. Original.

Renowned DAX experts Alberto Ferrari and Marco Russo teach you how to design data models for maximum efficiency and effectiveness.

 

How can you use Excel and Power BI to gain real insights into your information? As you examine your data, how do you write a formula that provides the numbers you need? The answers to both of these questions lie with the data model. This book introduces the basic techniques for shaping data models in Excel and Power BI. It’s meant for readers who are new to data modeling as well as for experienced data modelers looking for tips from the experts. If you want to use Power BI or Excel to analyze data, the many real-world examples in this book will help you look at your reports in a different way—like experienced data modelers do. As you’ll soon see, with the right data model, the correct answer is always a simple one!

 

By reading this book, you will:

• Gain an understanding of the basics of data modeling, including tables, relationships, and keys

• Familiarize yourself with star schemas, snowflakes, and common modeling techniques

• Learn the importance of granularity

• Discover how to use multiple fact tables, like sales and purchases, in a complex data model

• Manage calendar-related calculations by using date tables

• Track historical attributes, like previous addresses of customers or manager assignments

• Use snapshots to compute quantity on hand

• Work with multiple currencies in the most efficient way

• Analyze events that have durations, including overlapping durations

• Learn what data model you need to answer your specific business questions


About This Book

• For Excel and Power BI users who want to exploit the full power of their favorite tools

• For BI professionals seeking new ideas for modeling data

Introduction ix
Chapter 1 Introduction to data modeling
1(22)
Working with a single table
2(5)
Introducing the data model
7(8)
Introducing star schemas
15(5)
Understanding the importance of naming objects
20(1)
Conclusions
21(2)
Chapter 2 Using header/detail tables
23(12)
Introducing header/detail
23(1)
Aggregating values from the header
24(6)
Flattening header/detail
30(3)
Conclusions
33(2)
Chapter 3 Using multiple fact tables
35(20)
Using denormalized fact tables
35(5)
Filtering across dimensions
40(3)
Understanding model ambiguity
43(2)
Using orders and invoices
45(8)
Calculating the total invoiced for the customer
50(1)
Calculating the number of invoices that include the given order of the given customer
50(1)
Calculating the amount of the order, if invoiced
50(3)
Conclusions
53(2)
Chapter 4 Working with date and time
55(36)
Creating a date dimension
55(3)
Understanding automatic time dimensions
58(3)
Automatic time grouping in Excel
58(2)
Automatic time grouping in Power BI Desktop
60(1)
Using multiple date dimensions
61(5)
Handling date and time
66(2)
Time-intelligence calculations
68(1)
Handling fiscal calendars
69(3)
Computing with working days
72(6)
Working days in a single country or region
72(2)
Working with multiple countries or regions
74(4)
Handling special periods of the year
78(6)
Using non-overlapping periods
79(1)
Periods relative to today
80(2)
Using overlapping periods
82(2)
Working with weekly calendars
84(5)
Conclusions
89(2)
Chapter 5 Tracking historical attributes
91(20)
Introducing slowly changing dimensions
91(5)
Using slowly changing dimensions
96(3)
Loading slowly changing dimensions
99(7)
Fixing granularity in the dimension
102(2)
Fixing granularity in the fact table
104(2)
Rapidly changing dimensions
106(3)
Choosing the right modeling technique
109(1)
Conclusions
110(1)
Chapter 6 Using snapshots
111(16)
Using data that you cannot aggregate over time
111(1)
Aggregating snapshots
112(6)
Understanding derived snapshots
118(1)
Understanding the transition matrix
119(6)
Conclusions
125(2)
Chapter 7 Analyzing date and time intervals
127(26)
Introduction to temporal data
127(2)
Aggregating with simple intervals
129(2)
Intervals crossing dates
131(4)
Modeling working shifts and time shifting
135(2)
Analyzing active events
137(8)
Mixing different durations
145(6)
Conclusions
151(2)
Chapter 8 Many-to-many relationships
153(20)
Introducing many-to-many relationships
153(5)
Understanding the bidirectional pattern
155(2)
Understanding non-additivity
157(1)
Cascading many-to-many
158(3)
Temporal many-to-many
161(6)
Reallocating factors and percentages
164(2)
Materializing many-to-many
166(1)
Using the fact tables as a bridge
167(1)
Performance considerations
168(3)
Conclusions
171(2)
Chapter 9 Working with different granularity
173(16)
Introduction to granularity
173(2)
Relationships at different granularity
175(12)
Analyzing budget data
175(2)
Using DAX code to move filters
177(2)
Filtering through relationships
179(2)
Hiding values at the wrong granularity
181(4)
Allocating values at a higher granularity
185(2)
Conclusions
187(2)
Chapter 10 Segmentation data models
189(14)
Computing multiple-column relationships
189(3)
Computing static segmentation
192(2)
Using dynamic segmentation
194(2)
Understanding the power of calculated columns: ABC analysis
196(5)
Conclusions
201(2)
Chapter 11 Working with multiple currencies
203(12)
Understanding different scenarios
203(1)
Multiple source currencies, single reporting currency
204(4)
Single source currency, multiple reporting currencies
208(4)
Multiple source currencies, multiple reporting currencies
212(2)
Conclusions
214(1)
Appendix A Data modeling 101
215(12)
Tables
215(2)
Data types
217(1)
Relationships
217(1)
Filtering and cross-filtering
218(3)
Different types of models
221(4)
Star schema
222(1)
Snowflake schema
222(2)
Models with bridge tables
224(1)
Measures and additivity
225(1)
Additive measures
225(1)
Non-additive measures
225(1)
Semi-additive measures
225(2)
Index 227
Alberto Ferrari and Marco Russo are the founders of sqlbi.com, where they regularly publish articles about Microsoft Power Pivot, Power BI, DAX, and SQL Server Analysis Services. Both Ferrari and Russo provide consultancy and mentoring on business intelligence (BI). They are also frequent speakers at major international conferences, including Microsoft Ignite, PASS Summit, and SQLBits.
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